Overview

Brought to you by YData

Dataset statistics

Number of variables12
Number of observations2774
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory281.7 KiB
Average record size in memory104.0 B

Variable types

Numeric12

Alerts

avg_basket_size is highly overall correlated with gross_revenue and 1 other fieldsHigh correlation
avg_recency_days is highly overall correlated with frequencyHigh correlation
avg_ticket is highly overall correlated with avg_unique_basket_sizeHigh correlation
avg_unique_basket_size is highly overall correlated with avg_ticket and 1 other fieldsHigh correlation
frequency is highly overall correlated with avg_recency_daysHigh correlation
gross_revenue is highly overall correlated with avg_basket_size and 3 other fieldsHigh correlation
qtde_produtcs is highly overall correlated with avg_unique_basket_size and 3 other fieldsHigh correlation
qte_invoices is highly overall correlated with gross_revenue and 2 other fieldsHigh correlation
qte_items is highly overall correlated with avg_basket_size and 3 other fieldsHigh correlation
avg_ticket is highly skewed (γ1 = 51.90076813) Skewed
frequency is highly skewed (γ1 = 46.08548575) Skewed
qtde_returns is highly skewed (γ1 = 50.10197766) Skewed
avg_basket_size is highly skewed (γ1 = 44.87225707) Skewed
customer_id has unique values Unique
recency_days has 34 (1.2%) zeros Zeros
qtde_returns has 1481 (53.4%) zeros Zeros

Reproduction

Analysis started2025-04-09 18:26:19.235133
Analysis finished2025-04-09 18:27:22.866036
Duration1 minute and 3.63 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

Unique 

Distinct2774
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15285.7
Minimum12347
Maximum18287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T15:27:23.335448image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum12347
5-th percentile12626.65
Q113815.25
median15242.5
Q316779.75
95-th percentile17950.35
Maximum18287
Range5940
Interquartile range (IQR)2964.5

Descriptive statistics

Standard deviation1714.9849
Coefficient of variation (CV)0.11219538
Kurtosis-1.2069151
Mean15285.7
Median Absolute Deviation (MAD)1483.5
Skewness0.015990788
Sum42402531
Variance2941173.2
MonotonicityNot monotonic
2025-04-09T15:27:23.920008image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17850 1
 
< 0.1%
14482 1
 
< 0.1%
17058 1
 
< 0.1%
17704 1
 
< 0.1%
16933 1
 
< 0.1%
13772 1
 
< 0.1%
16249 1
 
< 0.1%
14198 1
 
< 0.1%
13989 1
 
< 0.1%
17930 1
 
< 0.1%
Other values (2764) 2764
99.6%
ValueCountFrequency (%)
12347 1
< 0.1%
12348 1
< 0.1%
12352 1
< 0.1%
12356 1
< 0.1%
12358 1
< 0.1%
12359 1
< 0.1%
12360 1
< 0.1%
12362 1
< 0.1%
12364 1
< 0.1%
12370 1
< 0.1%
ValueCountFrequency (%)
18287 1
< 0.1%
18283 1
< 0.1%
18282 1
< 0.1%
18273 1
< 0.1%
18272 1
< 0.1%
18270 1
< 0.1%
18265 1
< 0.1%
18263 1
< 0.1%
18261 1
< 0.1%
18260 1
< 0.1%

gross_revenue
Real number (ℝ)

High correlation 

Distinct2760
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2904.6492
Minimum36.56
Maximum279138.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T15:27:24.480817image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum36.56
5-th percentile264.557
Q1628.195
median1170.87
Q32423.86
95-th percentile7579.4915
Maximum279138.02
Range279101.46
Interquartile range (IQR)1795.665

Descriptive statistics

Standard deviation10927.083
Coefficient of variation (CV)3.7619287
Kurtosis331.96378
Mean2904.6492
Median Absolute Deviation (MAD)690.475
Skewness16.261241
Sum8057496.7
Variance1.1940114 × 108
MonotonicityNot monotonic
2025-04-09T15:27:25.041971image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1025.44 2
 
0.1%
745.06 2
 
0.1%
598.2 2
 
0.1%
1078.96 2
 
0.1%
731.9 2
 
0.1%
1353.74 2
 
0.1%
2053.02 2
 
0.1%
379.65 2
 
0.1%
1314.45 2
 
0.1%
331 2
 
0.1%
Other values (2750) 2754
99.3%
ValueCountFrequency (%)
36.56 1
< 0.1%
52 1
< 0.1%
52.2 1
< 0.1%
62.43 1
< 0.1%
68.84 1
< 0.1%
70.02 1
< 0.1%
77.4 1
< 0.1%
84.65 1
< 0.1%
90.3 1
< 0.1%
93.35 1
< 0.1%
ValueCountFrequency (%)
279138.02 1
< 0.1%
259657.3 1
< 0.1%
194550.79 1
< 0.1%
168472.5 1
< 0.1%
140438.72 1
< 0.1%
124564.53 1
< 0.1%
117375.63 1
< 0.1%
91062.38 1
< 0.1%
72882.09 1
< 0.1%
66653.56 1
< 0.1%

recency_days
Real number (ℝ)

Zeros 

Distinct252
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.627974
Minimum0
Maximum372
Zeros34
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T15:27:25.627150image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q110
median29
Q373
95-th percentile211
Maximum372
Range372
Interquartile range (IQR)63

Descriptive statistics

Standard deviation68.419023
Coefficient of variation (CV)1.2082195
Kurtosis3.4321191
Mean56.627974
Median Absolute Deviation (MAD)23.5
Skewness1.8983643
Sum157086
Variance4681.1627
MonotonicityNot monotonic
2025-04-09T15:27:26.383468image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 99
 
3.6%
4 87
 
3.1%
2 85
 
3.1%
3 85
 
3.1%
8 76
 
2.7%
10 67
 
2.4%
9 66
 
2.4%
7 65
 
2.3%
17 62
 
2.2%
22 55
 
2.0%
Other values (242) 2027
73.1%
ValueCountFrequency (%)
0 34
 
1.2%
1 99
3.6%
2 85
3.1%
3 85
3.1%
4 87
3.1%
5 43
1.6%
7 65
2.3%
8 76
2.7%
9 66
2.4%
10 67
2.4%
ValueCountFrequency (%)
372 1
 
< 0.1%
366 1
 
< 0.1%
360 1
 
< 0.1%
358 3
0.1%
354 1
 
< 0.1%
337 1
 
< 0.1%
336 2
0.1%
334 1
 
< 0.1%
333 2
0.1%
330 1
 
< 0.1%

qte_invoices
Real number (ℝ)

High correlation 

Distinct55
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0529921
Minimum2
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T15:27:27.004122image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q12
median4
Q36
95-th percentile17
Maximum206
Range204
Interquartile range (IQR)4

Descriptive statistics

Standard deviation9.071603
Coefficient of variation (CV)1.4986973
Kurtosis183.94516
Mean6.0529921
Median Absolute Deviation (MAD)2
Skewness10.624664
Sum16791
Variance82.293981
MonotonicityNot monotonic
2025-04-09T15:27:27.630008image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 781
28.2%
3 498
18.0%
4 393
14.2%
5 237
 
8.5%
6 173
 
6.2%
7 138
 
5.0%
8 98
 
3.5%
9 69
 
2.5%
10 55
 
2.0%
11 54
 
1.9%
Other values (45) 278
 
10.0%
ValueCountFrequency (%)
2 781
28.2%
3 498
18.0%
4 393
14.2%
5 237
 
8.5%
6 173
 
6.2%
7 138
 
5.0%
8 98
 
3.5%
9 69
 
2.5%
10 55
 
2.0%
11 54
 
1.9%
ValueCountFrequency (%)
206 1
< 0.1%
199 1
< 0.1%
124 1
< 0.1%
97 1
< 0.1%
91 2
0.1%
86 1
< 0.1%
72 1
< 0.1%
62 2
0.1%
60 1
< 0.1%
57 1
< 0.1%

qte_items
Real number (ℝ)

High correlation 

Distinct1632
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1697.8205
Minimum2
Maximum196844
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T15:27:28.243909image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile119
Q1330.25
median699.5
Q31478
95-th percentile4645.5
Maximum196844
Range196842
Interquartile range (IQR)1147.75

Descriptive statistics

Standard deviation6074.4301
Coefficient of variation (CV)3.5777812
Kurtosis438.72722
Mean1697.8205
Median Absolute Deviation (MAD)449
Skewness17.339197
Sum4709754
Variance36898701
MonotonicityNot monotonic
2025-04-09T15:27:28.867885image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
310 11
 
0.4%
246 8
 
0.3%
150 8
 
0.3%
200 7
 
0.3%
219 7
 
0.3%
260 7
 
0.3%
394 7
 
0.3%
272 7
 
0.3%
516 7
 
0.3%
300 7
 
0.3%
Other values (1622) 2698
97.3%
ValueCountFrequency (%)
2 1
< 0.1%
16 1
< 0.1%
17 1
< 0.1%
19 1
< 0.1%
20 1
< 0.1%
25 1
< 0.1%
27 2
0.1%
30 1
< 0.1%
32 1
< 0.1%
33 2
0.1%
ValueCountFrequency (%)
196844 1
< 0.1%
80997 1
< 0.1%
79963 1
< 0.1%
77373 1
< 0.1%
69993 1
< 0.1%
64549 1
< 0.1%
64124 1
< 0.1%
62812 1
< 0.1%
58243 1
< 0.1%
57785 1
< 0.1%

qtde_produtcs
Real number (ℝ)

High correlation 

Distinct468
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.72314
Minimum2
Maximum7837
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T15:27:29.528962image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile10
Q134
median72
Q3143
95-th percentile400.05
Maximum7837
Range7835
Interquartile range (IQR)109

Descriptive statistics

Standard deviation277.72934
Coefficient of variation (CV)2.140939
Kurtosis336.80085
Mean129.72314
Median Absolute Deviation (MAD)45
Skewness15.347204
Sum359852
Variance77133.584
MonotonicityNot monotonic
2025-04-09T15:27:30.154234image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 40
 
1.4%
35 34
 
1.2%
27 30
 
1.1%
26 30
 
1.1%
29 28
 
1.0%
31 27
 
1.0%
15 27
 
1.0%
33 27
 
1.0%
25 26
 
0.9%
42 26
 
0.9%
Other values (458) 2479
89.4%
ValueCountFrequency (%)
2 11
0.4%
3 13
0.5%
4 16
0.6%
5 16
0.6%
6 24
0.9%
7 14
0.5%
8 13
0.5%
9 20
0.7%
10 18
0.6%
11 23
0.8%
ValueCountFrequency (%)
7837 1
< 0.1%
5670 1
< 0.1%
5095 1
< 0.1%
4577 1
< 0.1%
2698 1
< 0.1%
2379 1
< 0.1%
2060 1
< 0.1%
1818 1
< 0.1%
1673 1
< 0.1%
1636 1
< 0.1%

avg_ticket
Real number (ℝ)

High correlation  Skewed 

Distinct2772
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.33923
Minimum2.1505882
Maximum56157.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T15:27:30.769089image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum2.1505882
5-th percentile4.8527022
Q112.426548
median17.946876
Q325.074658
95-th percentile88.427443
Maximum56157.5
Range56155.349
Interquartile range (IQR)12.64811

Descriptive statistics

Standard deviation1071.0491
Coefficient of variation (CV)20.463601
Kurtosis2718.3215
Mean52.33923
Median Absolute Deviation (MAD)6.3338406
Skewness51.900768
Sum145189.02
Variance1147146.2
MonotonicityNot monotonic
2025-04-09T15:27:31.322851image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.47833333 2
 
0.1%
4.162 2
 
0.1%
6.269700855 1
 
< 0.1%
32.59775 1
 
< 0.1%
19.03048387 1
 
< 0.1%
28.55451613 1
 
< 0.1%
12.80068182 1
 
< 0.1%
6.396214689 1
 
< 0.1%
26.08797101 1
 
< 0.1%
17.98461538 1
 
< 0.1%
Other values (2762) 2762
99.6%
ValueCountFrequency (%)
2.150588235 1
< 0.1%
2.4325 1
< 0.1%
2.462371134 1
< 0.1%
2.511241379 1
< 0.1%
2.515333333 1
< 0.1%
2.65 1
< 0.1%
2.656931818 1
< 0.1%
2.707598253 1
< 0.1%
2.760621572 1
< 0.1%
2.770464191 1
< 0.1%
ValueCountFrequency (%)
56157.5 1
< 0.1%
4453.43 1
< 0.1%
1687.2 1
< 0.1%
952.9875 1
< 0.1%
872.13 1
< 0.1%
841.0214493 1
< 0.1%
651.1683333 1
< 0.1%
640 1
< 0.1%
624.4 1
< 0.1%
615.75 1
< 0.1%

avg_recency_days
Real number (ℝ)

High correlation 

Distinct1155
Distinct (%)41.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.801889
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T15:27:31.798391image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13
Q134.241667
median59
Q399
95-th percentile224
Maximum366
Range365
Interquartile range (IQR)64.758333

Descriptive statistics

Standard deviation66.515011
Coefficient of variation (CV)0.84407889
Kurtosis3.6744362
Mean78.801889
Median Absolute Deviation (MAD)30
Skewness1.8283611
Sum218596.44
Variance4424.2467
MonotonicityNot monotonic
2025-04-09T15:27:32.213634image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
70 21
 
0.8%
46 18
 
0.6%
55 17
 
0.6%
31 16
 
0.6%
91 16
 
0.6%
49 16
 
0.6%
21 15
 
0.5%
42 15
 
0.5%
35 15
 
0.5%
14 14
 
0.5%
Other values (1145) 2611
94.1%
ValueCountFrequency (%)
1 9
0.3%
2 4
0.1%
2.861538462 1
 
< 0.1%
3 6
0.2%
3.330357143 1
 
< 0.1%
3.351351351 1
 
< 0.1%
4 5
0.2%
4.191011236 1
 
< 0.1%
4.275862069 1
 
< 0.1%
4.5 1
 
< 0.1%
ValueCountFrequency (%)
366 1
 
< 0.1%
365 1
 
< 0.1%
364 1
 
< 0.1%
363 1
 
< 0.1%
357 2
0.1%
356 1
 
< 0.1%
355 2
0.1%
352 1
 
< 0.1%
351 2
0.1%
350 3
0.1%

frequency
Real number (ℝ)

High correlation  Skewed 

Distinct1225
Distinct (%)44.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.049692192
Minimum0.0054495913
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T15:27:32.625968image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0.0054495913
5-th percentile0.0087463557
Q10.015758392
median0.024390244
Q30.041666667
95-th percentile0.11538462
Maximum17
Range16.99455
Interquartile range (IQR)0.025908275

Descriptive statistics

Standard deviation0.337595
Coefficient of variation (CV)6.7937233
Kurtosis2296.5219
Mean0.049692192
Median Absolute Deviation (MAD)0.010694545
Skewness46.085486
Sum137.84614
Variance0.11397038
MonotonicityNot monotonic
2025-04-09T15:27:33.037268image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0625 17
 
0.6%
0.02777777778 17
 
0.6%
0.02380952381 16
 
0.6%
0.08333333333 15
 
0.5%
0.09090909091 15
 
0.5%
0.03448275862 14
 
0.5%
0.02941176471 14
 
0.5%
0.07692307692 13
 
0.5%
0.02127659574 13
 
0.5%
0.02564102564 13
 
0.5%
Other values (1215) 2627
94.7%
ValueCountFrequency (%)
0.005449591281 1
 
< 0.1%
0.005464480874 1
 
< 0.1%
0.005479452055 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005586592179 2
0.1%
0.005602240896 1
 
< 0.1%
0.005617977528 2
0.1%
0.00566572238 1
 
< 0.1%
0.005681818182 2
0.1%
0.005698005698 3
0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
3 1
 
< 0.1%
2 1
 
< 0.1%
1.142857143 1
 
< 0.1%
1 8
0.3%
0.75 1
 
< 0.1%
0.6666666667 3
 
0.1%
0.550802139 1
 
< 0.1%
0.5335120643 1
 
< 0.1%
0.5 3
 
0.1%

qtde_returns
Real number (ℝ)

Skewed  Zeros 

Distinct205
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.158976
Minimum0
Maximum80995
Zeros1481
Zeros (%)53.4%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T15:27:33.454262image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q39
95-th percentile98
Maximum80995
Range80995
Interquartile range (IQR)9

Descriptive statistics

Standard deviation1564.3935
Coefficient of variation (CV)24.383081
Kurtosis2586.2541
Mean64.158976
Median Absolute Deviation (MAD)0
Skewness50.101978
Sum177977
Variance2447327.1
MonotonicityNot monotonic
2025-04-09T15:27:33.878725image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1481
53.4%
1 129
 
4.7%
2 117
 
4.2%
3 82
 
3.0%
4 72
 
2.6%
6 63
 
2.3%
5 55
 
2.0%
12 45
 
1.6%
8 39
 
1.4%
9 38
 
1.4%
Other values (195) 653
23.5%
ValueCountFrequency (%)
0 1481
53.4%
1 129
 
4.7%
2 117
 
4.2%
3 82
 
3.0%
4 72
 
2.6%
5 55
 
2.0%
6 63
 
2.3%
7 38
 
1.4%
8 39
 
1.4%
9 38
 
1.4%
ValueCountFrequency (%)
80995 1
< 0.1%
9014 1
< 0.1%
8004 1
< 0.1%
4427 1
< 0.1%
3768 1
< 0.1%
3332 1
< 0.1%
2878 1
< 0.1%
2022 1
< 0.1%
2012 1
< 0.1%
1776 1
< 0.1%

avg_basket_size
Real number (ℝ)

High correlation  Skewed 

Distinct1932
Distinct (%)69.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean245.46514
Minimum1
Maximum40498.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T15:27:34.316771image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile45
Q1103.33333
median172
Q3278.17381
95-th percentile585.55
Maximum40498.5
Range40497.5
Interquartile range (IQR)174.84048

Descriptive statistics

Standard deviation808.02308
Coefficient of variation (CV)3.2918039
Kurtosis2224.0987
Mean245.46514
Median Absolute Deviation (MAD)81
Skewness44.872257
Sum680920.29
Variance652901.3
MonotonicityNot monotonic
2025-04-09T15:27:34.756578image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 11
 
0.4%
86 9
 
0.3%
60 8
 
0.3%
75 8
 
0.3%
82 7
 
0.3%
208 7
 
0.3%
105 7
 
0.3%
136 7
 
0.3%
197 7
 
0.3%
73 7
 
0.3%
Other values (1922) 2696
97.2%
ValueCountFrequency (%)
1 1
< 0.1%
3.333333333 1
< 0.1%
5.333333333 1
< 0.1%
5.666666667 1
< 0.1%
6.142857143 1
< 0.1%
7.5 1
< 0.1%
9 1
< 0.1%
9.5 1
< 0.1%
11 1
< 0.1%
11.875 1
< 0.1%
ValueCountFrequency (%)
40498.5 1
< 0.1%
6009.333333 1
< 0.1%
3868.65 1
< 0.1%
2880 1
< 0.1%
2733.944444 1
< 0.1%
2518.769231 1
< 0.1%
2160.333333 1
< 0.1%
2082.225806 1
< 0.1%
2000 1
< 0.1%
1903.5 1
< 0.1%

avg_unique_basket_size
Real number (ℝ)

High correlation 

Distinct902
Distinct (%)32.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.135898
Minimum0.2
Maximum177
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T15:27:35.169811image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile2
Q17.5113636
median13.5
Q322
95-th percentile45.0875
Maximum177
Range176.8
Interquartile range (IQR)14.488636

Descriptive statistics

Standard deviation14.265567
Coefficient of variation (CV)0.83249604
Kurtosis9.9898011
Mean17.135898
Median Absolute Deviation (MAD)6.6666667
Skewness2.2440267
Sum47534.982
Variance203.50641
MonotonicityNot monotonic
2025-04-09T15:27:35.585883image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 34
 
1.2%
8 34
 
1.2%
16 34
 
1.2%
9 33
 
1.2%
7 32
 
1.2%
12 30
 
1.1%
18.5 29
 
1.0%
6 29
 
1.0%
7.5 28
 
1.0%
17 28
 
1.0%
Other values (892) 2463
88.8%
ValueCountFrequency (%)
0.2 1
 
< 0.1%
0.25 3
 
0.1%
0.3333333333 6
0.2%
0.4 1
 
< 0.1%
0.4090909091 1
 
< 0.1%
0.5 12
0.4%
0.5454545455 1
 
< 0.1%
0.5555555556 1
 
< 0.1%
0.5714285714 1
 
< 0.1%
0.6176470588 1
 
< 0.1%
ValueCountFrequency (%)
177 1
< 0.1%
105 1
< 0.1%
104 1
< 0.1%
98 1
< 0.1%
95.5 1
< 0.1%
94.33333333 1
< 0.1%
93 1
< 0.1%
89.625 1
< 0.1%
87 1
< 0.1%
85.66666667 1
< 0.1%

Interactions

2025-04-09T15:27:16.330811image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:20.246267image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:24.975178image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:30.460634image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:35.813221image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:41.013100image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:46.161129image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:51.241173image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:56.027986image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:00.982629image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:05.838961image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:11.079663image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:16.752855image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:20.683356image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:25.388850image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:30.920347image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:36.244389image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:41.426722image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:46.610978image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:51.613325image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:56.440872image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:01.389094image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:06.229680image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:11.497206image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:17.195030image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:21.053309image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:25.780374image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:31.336750image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:36.645234image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:41.885067image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:47.007692image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:51.973607image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:56.839487image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:01.758254image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:06.612978image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:11.920426image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:17.600224image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:21.454356image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:26.185124image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:31.781188image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:37.047760image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:42.313585image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:47.499181image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:52.359638image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:57.258209image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:02.156075image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:07.060419image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:12.379228image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:18.028348image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:21.830519image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:26.691660image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:32.208245image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:37.466240image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:42.746298image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:47.919550image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:52.755671image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:57.697834image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:02.583607image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:07.499230image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:12.800828image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:18.469887image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:22.303329image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:27.149951image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:32.620410image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:37.896256image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:43.179921image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:48.341125image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:53.159305image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:58.160374image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:02.996700image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:08.005860image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:13.239879image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:18.893816image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:22.715992image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:27.591130image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:33.116401image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:38.447378image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:43.603908image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:48.763448image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:53.561944image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:58.576694image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:03.409161image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:08.448943image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:13.674745image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:19.279397image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:23.050723image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:28.097732image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:33.517513image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:38.837367image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:43.983360image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:49.144601image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:53.933833image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:58.961212image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:03.802886image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:08.842514image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:14.072854image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:19.681325image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:23.409298image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:28.607165image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:33.962941image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:39.248935image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:44.400399image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:49.574639image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:54.316325image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:59.369099image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:04.197349image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:09.256671image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:14.491493image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:20.095825image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:23.768018image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:29.022085image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:34.386056image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:39.682063image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:44.809032image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:49.989981image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:54.727177image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:59.756586image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:04.592102image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:09.698168image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:14.914421image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:20.508996image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:24.214205image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:29.516003image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:34.812725image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:40.124942image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:45.229636image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:50.426341image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:55.130804image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:00.173765image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:04.998021image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:10.120976image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:15.344042image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:20.931159image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:24.618890image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:30.013372image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:35.300663image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:40.577217image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:45.661917image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:50.843268image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:26:55.623131image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:00.581874image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:05.420599image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:10.545660image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T15:27:15.887826image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Correlations

2025-04-09T15:27:35.882147image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
avg_basket_sizeavg_recency_daysavg_ticketavg_unique_basket_sizecustomer_idfrequencygross_revenueqtde_produtcsqtde_returnsqte_invoicesqte_itemsrecency_days
avg_basket_size1.000-0.0420.1990.383-0.1200.0250.6020.4020.2150.1250.759-0.104
avg_recency_days-0.0421.000-0.0790.186-0.012-0.952-0.366-0.301-0.214-0.477-0.3420.223
avg_ticket0.199-0.0791.000-0.639-0.1410.0810.274-0.3820.1890.0900.1960.034
avg_unique_basket_size0.3830.186-0.6391.000-0.001-0.1650.1020.547-0.065-0.1790.1460.006
customer_id-0.120-0.012-0.141-0.0011.0000.013-0.0850.012-0.0580.013-0.0780.013
frequency0.025-0.9520.081-0.1650.0131.0000.2580.2020.1750.3220.239-0.126
gross_revenue0.602-0.3660.2740.102-0.0850.2581.0000.7220.4620.7620.922-0.374
qtde_produtcs0.402-0.301-0.3820.5470.0120.2020.7221.0000.3280.6590.707-0.391
qtde_returns0.215-0.2140.189-0.065-0.0580.1750.4620.3281.0000.4250.427-0.187
qte_invoices0.125-0.4770.090-0.1790.0130.3220.7620.6590.4251.0000.703-0.447
qte_items0.759-0.3420.1960.146-0.0780.2390.9220.7070.4270.7031.000-0.366
recency_days-0.1040.2230.0340.0060.013-0.126-0.374-0.391-0.187-0.447-0.3661.000

Missing values

2025-04-09T15:27:21.804276image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
A simple visualization of nullity by column.
2025-04-09T15:27:22.539268image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

customer_idgross_revenuerecency_daysqte_invoicesqte_itemsqtde_produtcsavg_ticketavg_recency_daysfrequencyqtde_returnsavg_basket_sizeavg_unique_basket_size
0178505391.21372.034.01733.0297.018.1522221.00000017.00000040.050.9705880.617647
1130473232.5956.09.01390.0171.018.90403552.8333330.02830235.0154.44444411.666667
2125836705.382.015.05028.0232.028.90250026.5000000.04032350.0335.2000007.600000
313748948.2595.05.0439.028.033.86607192.6666670.0179210.087.8000004.800000
415100876.00333.03.080.03.0292.00000020.0000000.07317122.026.6666670.333333
5152914623.3025.014.02102.0102.045.32647126.7692310.04011529.0150.1428574.357143
6146885630.877.021.03621.0327.017.21978619.2631580.057221399.0172.4285717.047619
7178095411.9116.012.02057.061.088.71983639.6666670.03352041.0171.4166673.833333
81531160767.900.091.038194.02379.025.5434644.1910110.243316474.0419.7142866.230769
9160982005.6387.07.0613.067.029.93477647.6666670.0243900.087.5714294.857143
customer_idgross_revenuerecency_daysqte_invoicesqte_itemsqtde_produtcsavg_ticketavg_recency_daysfrequencyqtde_returnsavg_basket_sizeavg_unique_basket_size
561117290525.243.02.0404.0102.05.14941213.00.1428570.0202.00000046.000000
56201478577.4010.02.084.03.025.8000005.00.3333330.042.0000001.000000
562117254272.444.02.0252.0112.02.43250011.00.1666670.0126.00000050.000000
563717232421.522.02.0203.036.011.70888912.00.1538460.0101.50000015.000000
563817468137.0010.02.0116.05.027.4000004.00.4000000.058.0000002.500000
564913596697.045.02.0406.0166.04.1990367.00.2500000.0203.00000066.500000
5655148931237.859.02.0799.073.016.9568492.00.6666670.0399.50000036.000000
568014126706.137.03.0508.015.047.0753333.00.75000050.0169.3333334.666667
5686135211092.391.03.0733.0435.02.5112414.50.3000000.0244.333333104.000000
569615060301.848.04.0262.0120.02.5153331.02.0000000.065.50000020.000000